Methods of biological network inference for reverse engineering cancer chemoresistance mechanisms

Drug Discovery Today

Volumn 19, Issue 2, 2014, Pages 151-163

  Lecca, Paola ^a  

^a UNIVERSITY OF TRENTO   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

GEMCITABINE; ANTINEOPLASTIC AGENT; DEOXYCYTIDINE;

BAYES THEOREM; CANCER CELL; CANCER CHEMOTHERAPY; CANCER RESISTANCE; CASE STUDY; DRUG METABOLISM; GENE EXPRESSION; GENE REGULATORY NETWORK; HUMAN; MOLECULAR BIOLOGY; PANCREAS CANCER; REVIEW; STOCHASTIC MODEL; ANALOGS AND DERIVATIVES; DRUG RESISTANCE; GENETICS; NEOPLASMS; PANCREATIC NEOPLASMS; PATHOLOGY; STATISTICS;

ANTINEOPLASTIC AGENTS; BAYES THEOREM; DEOXYCYTIDINE; DRUG RESISTANCE, NEOPLASM; HUMANS; NEOPLASMS; PANCREATIC NEOPLASMS; STOCHASTIC PROCESSES;

EID: 84895919029     PISSN: 13596446     EISSN: 18785832     Source Type: Journal    
DOI: 10.1016/j.drudis.2013.10.026     Document Type: Review

References (56)

1. Y. Nakai et al. Identifying genes with differential expression in gemcitabine-resistant pancreatic cancer cells using comprehensive transciptome analysis Oncol. Rep. 14 2005 1263 1267
2. J. Sato et al. Gene expression analysis for predicting gemcitabine resistance in human cholangiocacinoma J. Hepatobiliary Pancreat. Sci. 18 2011 700 711
3. F. Toffalorio et al. Expression of gemcitabine- and cisplatin- related genes in non-small-cell lung cancer Pharmacogenom. J. 10 2010 180 190
4. A.L. Hopkins Network pharmacology: the next paradigm in drug discovery Nat. Chem. Biol. 4 2008 682 690
5. C. Priami Algorithmic systems biology Commun. ACM 52 2009 80 88
6. Ingenuity home page: www.ingenuity.com, 2013.
7. I. Stelniec-Klotz et al. Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS Mol. Syst. Biol. 8 2012 601
8. B.P. Madhamshettiwar et al. Gene regulatory network inference: evaluation and application to ovarian cancer allows the prioritization of drug targets Genome Med. 4 2012 41
9. N. Tanaka, and G.A. Papoian Reverse-engineering of biochemical reaction networks from spatio-temporal correlations of fluorescence fluctuations J. Theor. Biol. 264 2 2010 490 500
10. A. Crombach et al. Efficient reverse-engineering of a developmental gene regulatory network PLoS Comput. Biol. 8 7 2012 e1002589
11. Biocarta: http://www.biocarta.com/, 2012.
12. KEGG Pathways Database: http://www.genome.jp/kegg/pathway.html, 2012.
13. REACTOME: http://www.reactome.org/ReactomeGWT/entrypoint.html, 2012.
14. NCBI Biosystem Database: http://www.ncbi.nlm.nih.gov/Structure/ biosystems/docs/biosystems-about.html, 2012.
15. PC Pathways Commons: http://www.pathwaycommons.org/pc/, 2012.
16. A.S. Azmi, Z. Wang, P.A. Philip, R.M. Mohammad, and F.H. Sarkar1 Proof of concept: a review on how network and systems biology approaches aid in the discovery of potent anticancer drug combinations Mol. Cancer Ther. 9 12 2010 3137 3144
17. V.A. Smith, E.D. Jarvis, and A.J. Hartemink Evaluating functional network inference using simulation of complex systems Bioinformatics 18 2002 S216 S224
18. S.-Y. Chao et al. An integrative approach to identify cancer chemoresistance-associated pathways BMC Med. Genomics 4 2011
19. A.-K. Mnull, A.J. Kangas, and P. Soininen Quantitative high-throughput metabolomics: a new era in epidemiology and genetics Genome Med. 4 2012
20. J. Han et al. Towards high-throughput metabolomics using ultrahigh-field Fourier transform ion cyclotron resonance mass spectrometry Metabolomics 4 2008 128 140
21. R. Kaddurah-Daouk, B.S. Kristal, and R.M. Weinshilboum Metabolomics: a global biochemical approach to drug response and disease Annu. Rev. Pharmacol. Toxicol. 48 2008 653 683
22. S. Heux et al. A high-throughput metabolomics method to predict high concentration cytotoxicity of drugs from low concentration profiles Metabolomics 8 2012 433 443
23. P. Baldi, and S. Brunak Bioinformatics. The Machine Learning Approach 2001 The MIT Press
24. S.A. Veltkamp et al. New insights into the pharmacology and cytotoxicity of gemcitabine and 2′, 2′-difluorodeoxyuridine Mol. Cancer Ther. 7 2008 2415 2425
25. M. Samoilov, A. Arkin, and J. Ross On the deduction of chemical reaction pathways from measurements of time series of concentration Chaos 11 2001 108 114
26. A. Ruttor, G. Sanguinetti, and M. Opper Approximate inference for stochastic reaction systems N.D. Lawrence, M. Girolami, M. Rattray, Learning and Inference in Computational and Systems Biology 1 edn 2010 MIT Press
27. N.D. Lawrence, M. Girolami, and M. Rattray et al. Learning and Inference in Computational and Systems Biology. 1st edn 2010 MIT Press
28. P. Lecca An integrative network inference approach to predict mechanisms of cancer chemoresistance Integr. Biol. 5 2013 458 473
29. P. Lecca et al. Inferring biochemical reaction pathways: the case of the gemcitabine pharmacokinetics BMC Syst. Biol. 6 2012
30. Y. Nakano et al. Gemcitabine chemoresistance and molecular markers associated with gemcitabine transport and metabolism in human pancreatic cancer cells Br. J. Cancer 96 2007 457 463
31. H. Fujita et al. Gene expression levels as predictive markers of outcome in pancreatic cancer after gemcitabine-based adjuvant chemotherapy Neoplasia 12 10 2010 807 817
32. S. Ohhashi et al. Down-regulation of deoxycytidine kinase enhances acquired resistance to gemcitabine in pancreatic cancer Anticancer Res. 28 2008 2205 2212
33. P. Lecca et al. Modelling and estimating dynamics of tumor shrinkage with Blenx and kinfer Proceedings of UKSim 2011 - 13th International Conference on Modelling and Simulation Cambridge, UK, August 2011 75 80
34. O. Kahramanogullari et al. Algorithmic modeling quantifies the complementary contribution of metabolic inhibitions to gemcitabine efficacy PloS One 2012 (in press)
35. C. Archambeau, and M. Opper Approximate Inference for Continuous-Time Markov Processes 2011 Cambridge University Press
36. D.G. Tzikas, A.C. Likas, and N.P. Galatsanos The variational approximation for Bayesian inference. Life after the EM algorithm Signal Process. Mag., IEEE 25 2008 131 146
37. D.J. Wilkinson Stochastic Modelling for Systems Biology 2006 CRC Press/Taylor & Francis Group
38. STRING database home page: http://string-db.org/.
39. E. Giovannetti et al. Transcription analysis of human equilibrative nucleoside transporter-1 predicts survival in pancreas cancer patients treated with gemcitabine Cancer Res. 66 2006 3928 3935
40. J. Spratlin et al. The absence of human equilibrative nucleoside transporter 1 is associated with reduced survival in patients with gemcitabine-treated pancreas adenocarcinoma Clin. Cancer Res. 10 2004 6956 6961
41. D.T. Gillespie A general method for numerically simulating the stochastic time evolution of coupled chemical species J. Comp. Phys. 22 1976 403 434
42. E. Chu, and V.T. DeVita Physicians' Cancer Chemotherapy Drug Manual 2007 Jones & Bartlett
43. R. Ashida et al. Gemcitabine sensitivity-related mRNA expression in endoscopic ultrasound-guided fine-needle aspiration biopsy of unresectable pancreatic cancer J. Exp. Clin. Cancer Res. 28 2009
44. R. Andersson et al. Gemcitabine chemoresistance in pancreatic cancer: molecular mechanisms and potential solutions Scand. J. Gastroenterol. 44 2009 782 786
45. M. Duxbury et al. Identification of novel channel and transporter genes associated with acquired gemcitabine resistance in pancreatic adenocarcinoma cells Poster session presented at Pharmaconference Switzerland 2003
46. S. Ina et al. Identifying molecular markers for chemosensitivity to gemcitabine in pancreatic cancer: increased expression of interferon-stimulated gene 15 kd is associated with intrinsic chemoresistance Pancreas 39 2010 473 485
47. D.R. Rauchwerger et al. Equilibrativesensitive nucleoside transporter and its role in gemcitabine sensitivity Cancer Res. 60 2000 6075 6079
48. M.P. Kim, and G.E. Gallick Gemcitabine resistance in pancreatic cancer: picking the key players Clin. Cancer Res. 14 2008 1284
49. W. Huanwen et al. Intrinsic chemoresistance to gemcitabine is associated with constitutive and laminin-induced phosphorylation of fak in pancreatic cancer cell lines Mol. Cancer 8 2009 125
50. J. Garcia-Manteiga et al. Nucleoside transporter profiles in human pancreatic cancer cells: role of hcnt1 in 20,20-difluorodeoxycytidine-induced cytotoxicity Clin. Cancer Res. 9 2003 5000 5008
51. J.L. Spratlin, and J.R. Mackey Human equilibrative nucleoside transporter 1 (hENT1) in pancreatic adenocarcinoma: towards individualized treatment decisions Cancers 2 2010 2044 2054
52. +-dependent nucleoside transporter (cnt) family: identification and characterization of novel human and mouse proteins (hcnt3 and mcnt3) broadly selective for purine and pyrimidine nucleosides (system cib) Mol. Membr. Biol. 18 2001 65 72
53. M.L. Whitfield et al. Identification of genes periodically expressed in the human cell cycle and their expression in tumors Mol. Biol. Cell 13 2002 1977 2000
54. Cyclebase: http://www.cyclebase.org/, 2012.
55. S. Réjiba et al. Gemcitabine-based chemogene therapy for pancreatic cancer using ad-dck::umk gdept and tsrr sirna strategies Neoplasia 7 2009 637 650
56. P. Carbonetto, and M. Stephens Scalable variational inference for Bayesian variable selection in regression, and its accuracy in genetic association studies Bayesian Anal. 7 2012 73 108